Objective:This study aims to analyze the three-dimensional(3D)quantitative param-eters of ground glass nodules(GGN)on CT scans,identify the optimal diagnostic indicators and their cut-off values for assessing the invasion risk of GGN smaller than 3cm,and explore their application value in preoperative evaluation.Methods:126 patients with pulmonary ground glass nodules smaller than 3cm diagnosed after surgical treatment were retrospectively collected from September 2021 to June 2022 in Ganzhou People's Hospital(Ganzhou Hospital Affiliated to Nanchang University).Based on the final pathological findings,the patients were divided into two distinct groups.Invasive adenocar-cinoma(IA)was included into high-risk group,while atypical adenomatous hyperplasia(AAH),ade-nocarcinoma in situ(AIS),and minimally invasive adenocarcinoma(MIA)were included into low-risk group.The 3D quantitative parameters of pulmonary ground-glass nodules,including 3D volume,3D average CT value,solid proportion of the nodules,were acquired using 3D technology for visualization.Parameters that can be used to predict the likelihood of invasion were selected,and their diagnostic value was subsequently evaluated.Results:A total of 126 patients were included in the study.70 indi-viduals were divided into the high-risk group,with a mean age of 57 years(range:49～62 years),and 56 patients were divieded into the low-risk group,with an average age of 50 years(range:40～54 years).Significantly difference of age distributions,nodule sizes and distributions were observed be-tween the high-risk and low-risk groups(P＜0.05).There were no significant differences in gender ratio and nodule location between the two groups(P＞0.05).Notably,all 3D quantitative parameters exhibited statistically significant differences between the high-risk and low-risk groups(P＜0.05).The receiver operating characteristic curves(ROC)of pulmonary GGN invasion risk indicated the fol-lowing optimal thresholds:11.85mm for long diameter,8.95mm for short diameter,1.351 for long di-ameter/short diameter ratio,-597.1HU for 3D mean CT value,447.75mm3 for 3D volume,0.403mg·mm-3 for 3D density,223.628mg for 3D mass,and 7.85％for the solid proportion of GGN.These thresholds served as predictive indicators for pulmonary GGN invasion risk.Especially when the three-dimensional volume of the lesion exceeded 447.75mm3,the sensitivity and specificity for predicting a high risk of pulmonary GGN were 81.4％and 69.6％,respectively.Binary Logistic re-gression analysis identified the 3D volume and solid proportion as independent predictors of pulmonary GGN invasion risk.Combining these two indicators further enhanced prediction accuracy and increase the area under the curve(AUC=0.826).Conclusion:The reasonable use of 3D visualization technolo-gy to obtain quantitative parameters such as 3D volume and quality of pulmonary nodules can effective-ly assist in the evaluation of invasion risk of GGN＜3cm.Combined with relevant clinical data,it has important guiding significance for the evaluation and judgment of preoperative strategy.
维普
万方数据